Abstract

This paper examined the use of the backpercolation neural network algorithm to identify mutated MODY3 gene sequence data that is responsible for type II (maturity onset) diabetes. It was then demonstrated that a supervised feed forward method gave more accurate results in predicting point mutation in genes than the neural network backpropagation method. This paper brought the technique to the attention of other researchers as to how the method can be used for this and for the prediction of other diseases. The technique had been widely used in analysing environmental data is now commonly used in Bioinformatics.